Browsing DMI Technical Reports by Issue Date
Now showing items 1-20 of 46
-
SSVM: A Amooth Support Vector Machine for Classification
(1999)Smoothing methods, extensively used for solving important math- ematical programming problems and applications, are applied here to generate and solve an unconstrained smooth reformulation of the support vector machine ... -
Large Scale Kernel Regression via Linear Programming
(1999)The problem of tolerant data tting by a nonlinear surface, in- duced by a kernel-based support vector machine [24], is formulated as a linear program with fewer number of variables than that of other linear programming ... -
Lagrangian Support Vector Machines
(2000)An implicit Lagrangian for the dual of a simple reformulation of the standard quadratic program of a linear support vector machine is proposed. This leads to the minimization of an unconstrained di erentiable convex ... -
Optimization of Gamma Knife Radiosurgery
(2000)The Gamma Knife is a highly specialized treatment unit that pro- vides an advanced stereotactic approach to the treatment of tumors, vascular malformations, and pain disorders within the head. Inside a shielded ... -
FATCOP 2.0: Advanced Features in an Opportunistic Mixed Integer Programming Solver
(2000)We describe FATCOP 2.0, a new parallel mixed integer program solver that works in an opportunistic computing environment provided by the Condor resource management system. We outline changes to the search strategy of ... -
A Practical Approach to Sample-path Simulation Optimization
(2000)We propose solving continuous parametric simulation optimizations using a deterministic nonlinear optimiza- tion algorithm and sample-path simulations. The op- timization problem is written in a modeling language with ... -
Data Selection for Support Vector Machine Classifiers
(2000)The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classi er, is formulated as a concave minimization problem and solved by a nite number ... -
Interior Point Methods for Massive Support Vector Machines
(2000-05-25)We investigate the use of interior point methods for solving quadratic programming problems with a small number of linear constraints where the quadratic term consists of a low-rank update to a positive semi-de nite matrix. ... -
Robust Linear and Support Vector Regression
(2000-09)The robust Huber M-estimator, a differentiable cost function that is quadratic for small errors and linear otherwise, is modeled exactly, in the original primal space of the problem, by an easily solvable simple convex ... -
Semismooth Support Vector Machines
(2000-11-29)The linear support vector machine can be posed as a quadratic pro- gram in a variety of ways. In this paper, we look at a formulation using the two-norm for the misclassi cation error that leads to a positive de - nite ... -
Slice Models in General Purpose Modeling Systems
(2000-12-14)Slice models are collections of mathematical programs with the same structure but di erent data. Examples of slice models appear in Data Envelopment Analysis, where they are used to evaluate e ciency, and cross-validation, ... -
Incremental Support Vector Machine Classi cation
(2001)Using a recently introduced proximal support vector ma- chine classi er [4], a very fast and simple incremental support vector machine (SVM) classi er is proposed which is capable of modifying an existing linear classi ... -
Survival-Time Classi cation of Breast Cancer Patients
(2001)The identi cation of breast cancer patients for whom chemother- apy could prolong survival time is treated here as a data mining prob- lem. This identi cation is achieved by clustering 253 breast cancer patients into ... -
Cross-Validation, Support Vector Machines and Slice Models
(2001)We show how to implement the cross-validation technique used in ma- chine learning as a slice model. We describe the formulation in terms of support vector machines and extend the GAMS/DEA interface to allow for e cient ... -
A Finite Newton Method for Classi cation Problems
(2001)A fundamental classi cation problem of data mining and machine learning is that of minimizing a strongly convex, piecewise quadratic function on the n-dimensional real space Rn. We show nite termination of a Newton ... -
Knowledge-Based Support Vector Machine Classi ers
(2001)Prior knowledge in the form of multiple polyhedral sets, each belonging to one of two categories, is introduced into a reformulation of a linear support vector machine classi er. The resulting formulation leads to a ... -
Set Containment Characterization
(2001)Characterization of the containment of a polyhedral set in a closed halfspace, a key factor in generating knowledge-based support vector machine classi ers [7], is extended to the following: (i) Containment of one ... -
Data Mining via Support Vector Machines
(2001)Support vector machines (SVMs) have played a key role in broad classes of problems arising in various elds. Much more recently, SVMs have become the tool of choice for problems arising in data classi - cation and mining. ... -
SIMULATION OPTIMIZATION BASED ON A HETEROGENEOUS COMPUTING ENVIRONMENT
(2001)We solve a simulation optimization using a deterministic nonlinear solver based on the sample-path concept. The method used a quadratic model built from a collection of surrounding simulation points. The scheme does not ... -
RSVM: Reduced Support Vector Machines
(2001-01)An algorithm is proposed which generates a nonlinear kernel-based separating surface that requires as little as 1% of a large dataset for its explicit evaluation. To generate this nonlinear surface, the entire dataset ...